基于甲襞微循环特征的结缔组织病患者肺动脉高压风险评估研究
doi: 10.7655/NYDXBNSN241263
周张迪1 , 张译心2 , 戴嘉懿2 , 李东玉1 , 孙晓萱1 , 王嫱1
1. 南京医科大学第一附属医院风湿免疫科
2. 心血管内科,江苏 南京 210029
基金项目: 国家重点基础研究发展计划(2021YFC2501305)
Exploring the risk of pulmonary arterial hypertension in patients with connective tissue disease based on nailfold video capillaroscopy
ZHOU Zhangdi1 , ZHANG Yixin2 , DAI Jiayi2 , LI Dongyu1 , SUN Xiaoxuan1 , WANG Qiang1
1. Department of Rheumatology
2. Department of Cardiology,the First Affiliated Hospital with Nanjing Medical University,Nanjing 210029 ,China
摘要
目的:本研究旨在评估甲襞微循环检测(nailfold video capillaroscopy,NVC)在结缔组织病(connective tissue disease, CTD)相关肺动脉高压(pulmonary arterial hypertension,PAH)患者诊断中的预测价值。方法:回顾性分析2022年9月—2024年6 月在南京医科大学第一附属医院风湿免疫科住院并行NVC的CTD患者147例。根据是否合并PAH,将患者分为CTD-PAH和 CTD-nonPAH两组。通过多因素Logistic回归分析筛选CTD患者发生PAH的危险因素。基于该多因素Logistic回归分析构建 Nomogram预测模型,并使用受试者工作特征曲线(receiver operating characteristic,ROC)进行模型性能评估。结果:CTD患者中 CTD-PAH 组 52 例(35.4%)。CTD-PAH 组患者的毛细血管袢长度较 CTD-nonPAH 组长[262.0(207.0,308.0)vs. 202.0(160.0, 272.0),P < 0.05],袢周积分高于CTD-nonPAH组[2.40(0.80,3.92)vs. 1.90(0.40,2.80),P < 0.05]。Logistic回归分析显示管袢长度长和袢周积分高均增加PAH发生的风险[OR=1.300(95%CI:1.100~1.500),OR=1.268(95%CI:1.025~1.568)]。Nomogram 预测模型ROC曲线下面积达0.705(95%CI:0.618~0.792,P < 0.05)。结论:甲襞毛细血管特征(包括毛细血管袢长度和袢周积分) 可能是结缔组织病患者发生肺动脉高压的独立预测因子,为CTD-PAH患者的早期筛查和个体化治疗策略提供了新的依据。
Abstract
Objective:This study aims to evaluate the predictive value of nailfold capillaroscopy(NVC)in the diagnosis of patients with connective tissue disease(CTD)associated pulmonary arterial hypertension(PAH). Methods:A retrospective analysis was conducted on 147 patients with connective tissue disease(CTD)who were hospitalised in the Department of Rheumatology and Immunology of the First Affiliated Hospital with Nanjing Medical University and underwent NVC from September 2022 to June 2024. According to whether they were combined with pulmonary arterial hypertension(PAH)or not,CTD patients were divided into two groups:CTD-PAH and CTD-nonPAH. Risk factors for PAH in CTD patients were screened by multifactorial logistic regression analysis. A nomogram prediction model was constructed based on this multifactorial logistic regression analysis and the model performance was evaluated using the receiver operating characteristic(ROC)curve. Results:Among the CTD patients,52(35.4%) were included in the CTD-PAH group. The capillary length was longer in the CTD-PAH group than in the CTD-nonPAH group[262.0 (207.0,308.0)vs. 202.0(160.0,272.0),P < 0.05],and the pericapillary score was higher than that in the CTD-nonPAH group[2.40 (0.80,3.92)vs. 1.90(0.40,2.80),P < 0.05]. Logistic regression analysis showed that both long capillary length and high pericapillary score increased the risk of PAH occurrence[OR=1.300(95% CI:1.100-1.500),OR=1.268(95%CI:1.025-1.568)]. The area under the ROC curve of the nomogram prediction model amounted to 0.705(95% CI:0.618-0.792,P < 0.05). Conclusion:The findings suggest that nailfold capillary characteristics,including capillary length and pericapillary score,may serve as independent predictors of PAH in patients with CTD. These results provide a new basis for early screening and individualized therapeutic strategies in CTD-PAH patients.
肺动脉高压(pulmonary arterial hypertension, PAH)是一种以肺血管重塑和肺血管阻力进行性升高为特征的综合征,可导致右心室肥大和重塑,最终可能因右心衰竭而导致死亡[1-2]。结缔组织病(connective tissue diseases,CTD)是导致 PAH 的主要相关因素之一,也是 CTD 患者的主要致死原因[3-4]。因此,如何早期识别 PAH 的发生具有重要意义。
甲襞微循环检测(nailfold video capillaroscopy, NVC)是一种无创、直观显示微血管病变的检查技术,能够反映机体微循环灌注状态,并在一定程度上反映全身各组织、器官及系统的大循环状况[5]。 CTD⁃PAH的病理机制主要以肺血管炎为特征,表现为肺小血管的炎性充血水肿、血管内壁增厚和血管重构狭窄[3],导致肺循环阻力显著升高,这与系统性红斑狼疮(systemic lupus erythematosus,SLE)患者皮肤小血管病变的表现相似且常常同步发生[6]。NVC 可以清晰地观察到甲襞毛细血管的管径、数量及形态的变化,以及红细胞聚集及渗出的程度和血流速度[7-8],故可能间接反映患者的肺血管病变情况。本研究旨在探讨CTD合并PAH患者中甲襞微循环的异常特征,及其与PAH发生的相关性,以期为早期筛查和个体化治疗提供新思路。
1 对象和方法
1.1 对象
回顾性分析2022年9月—2024年5月在南京医科大学第一附属医院风湿免疫科就诊并接受 NVC 的168例CTD患者。入选标准:①年龄≥18岁;②符合CTD诊断标准:SLE患者符合2012年系统性红斑狼疮国际临床协作组(Systemic Lupus International Collaborating Clinics,SLICC)分类标准[9];干燥综合征 (Sjögren’s syndrome,SS)患者符合2002年国际分类标准[10];系统性硬化症(systemic sclerosis,SSc)患者符合 2013 年美国风湿病学会/欧洲抗风湿病联盟 [American College of Rheumatology(ACR)/European League Against Rheumatism(EULAR)]分类标准[11]; 类风湿关节炎(rheumatoid arthritis,RA)患者符合 2009 年 ACR/EULAR 分类标准[12];混合型结缔组织病(mixed connective tissue disease,MCTD)患者符合 Alarcon⁃Segovia 标准[13] 或Kahn标准[14];排除因感染性疾病、肿瘤或药物因素引起的自身免疫抗体增高;③PAH 诊断标准为在海平面静息状态下,经右心漂浮导管(right heart catheterization,RHC)测得:平均肺动脉压(mean pulmonary arterial pressure, mPAP)>20 mmHg(1 mmHg=0.133 kPa),肺动脉楔压 (pulmonary artery wedge pressure,PAWP)≤15 mmHg,且肺血管阻力(pulmonary vascular resistance,PVR)>2 Wood单位(1 Wood单位=80 dyn·s·cm-5[2]
排除标准:①因左心疾病引起的 PAH,包括射血分数保留的心力衰竭、射血分数降低的心力衰竭、心脏瓣膜病以及先天性或获得性心血管疾病; ②严重的肺间质病变或慢性阻塞性肺疾病,表现为用力肺活量低于预计值的 60%,或高分辨率 CT 显示严重的肺间质纤维化,且第1秒用力肺活量低于预计值的70%提示存在慢性阻塞性肺疾病;③存在肺栓塞证据,如核素通气灌注显像高度提示肺栓塞,或 CT 肺动脉造影结果显示阳性;④肝硬化伴门静脉高压;⑤严重的血液系统疾病,如长期严重贫血或代谢性疾病;⑥长期服用可能引起 PAH 的药物或接触毒性物质,如甲基苯丙胺等;⑦人类免疫缺陷病毒(human immunodeficiency virus,HIV) 感染。
根据纳入及排除标准,本研究共纳入 147 例 CTD 患者。依据是否合并 PAH,将患者分为两组: CTD 合并 PAH(CTD ⁃ PAH)组 52 例,CTD 无 PAH (CTD⁃nonPAH)组95例。本研究已获得南京医科大学第一附属医院医学伦理委员会的批准(伦理审批编号:2023⁃SR⁃756)。患者均知情同意。
1.2 方法
1.2.1 资料收集
采用回顾性分析,收集所有患者的基线数据,内容包括:①一般信息,如年龄、性别、基础疾病类型、 CTD病程(首次确诊CTD至入组时的时间间隔)、PAH 病程及右心导管资料;②甲襞微循环参数。
1.2.2 NVC
在室温 20~25℃的环境下,受试者安静休息 10~20 min后取坐位。选择双手的食指、中指、无名指和小指,使用TR8000D型微循环显微检查仪依次进行观测(低倍镜放大 60 倍,高倍镜放大 200 倍),并拍摄典型图像和录像以供回放分析。在高倍镜下,测量指标包括甲襞毛细血管数量、输入支管径、输出支管径、袢顶管径及血流速度等。同时,记录甲襞毛细血管交叉、畸形管袢、出血、渗出、乳头、红细胞聚集、汗腺导管、不规则扩大毛细血管、巨型管袢以及有无分支血管/丛状血管等,并观察血管排列是否整齐或紊乱[8]。检查结果由至少2名主治医生进行综合分析,且分析专家对患者的病情情况保持不知情。
1.2.3 甲襞微循环状况评估
采用“田牛甲襞微循环加权积分法”对甲襞微循环状况进行评分和记录[715]。该方法主要依据形态、流态和袢周3个方面来评估。形态积分涉及清晰度、管袢数量、管径大小、袢顶直径、管袢长度、交叉情况和畸形管袢数量。流态积分关注流速、血管活动性、红细胞聚集程度、白细胞数量、白微栓和血色。袢周积分则包括渗出、出血、乳头下静脉丛、乳头和汗腺导管的情况。总积分由这3个积分总和而得。
正常的甲襞毛细血管形态为:毛细血管密度正常(≥7根/mm),毛细血管形态正常(发夹状、屈曲状、交叉1~2次),毛细血管袢径正常(袢径<20 μm),无大量融合性出血。正常情况下,毛细血管管袢长为 150~250 μm。若袢径>20 μm 则为扩张毛细血管; 若>50 μm则为巨大毛细血管[16]
1.3 统计学方法
采用R软件进行数据处理、分析及绘图。连续变量若符合正态分布,则以均数±标准差(x-±s)表示;若不符合正态分布,则以中位数(四分位数)[MP25P75)]表示。分类变量以例数(百分率)表示。为进一步分析CTD患者发生PAH的危险因素,采用多因素 Logistic 回归分析,并绘制受试者工作特征 (receiver operating characteristic,ROC)曲线以评估模型的预测效能。使用R包rms绘制预测模型的列线图和校准曲线,并进行 Hosmer⁃Lemeshow 拟合优度检验,以评估模型的准确性。不同组间的连续变量采用 t 检验或 Wilcoxon 秩和检验进行比较,分类变量则采用χ2 检验。
2 结果
2.1 CTD⁃PAH 组与 CTD⁃nonPAH 组人口学和临床特征比较
本研究共纳入147例CTD患者(表1),其中CTD ⁃PAH组52例(35.4%),女50例、男2例,中位年龄为 45.5 岁;CTD⁃nonPAH 组 95 例(64.6%),女 89 例、男 6 例,中位年龄为50.0岁。两组患者在性别、年龄、病程及原发病类型方面差异无统计学意义。然而, CTD⁃PAH 组患者的毛细血管袢长度及袢周积分显著高于CTD⁃nonPAH组(P均<0.05)。
2.2 Logistic回归分析CTD患者发生PAH危险因素
以CTD患者是否发生PAH作为因变量(1表示发生,0表示未发生),将表1中差异有统计学意义的管袢长度、袢周积分纳入 Logistic 回归模型进行分析。既往研究发现SSc/MCTD患者甲襞微循环较其他CTD患者更为严重,故将病种也纳入Logistic回归模型。结果显示,管袢长度和袢周积分均为 PAH 发生的独立危险因素。具体而言,管袢长度每增加50 μm,发生PAH的风险增加0.3倍;袢周积分每增加1分,发生PAH的风险增加0.268倍(表2)。
2.3 Nomogram构建CTD⁃PAH预测模型
根据多因素Logistic回归模型,估算了各危险因素的优势比(odds ratio,OR)及其95%置信区间。预测PAH风险的公式为P=eLP1+eLP。公式中的线性预测值(linear programming,LP)计算如下:若病种为 SSc/MCTD,LP=0.006×管袢长/50+ 0.237×袢周积分+ 0.883;若病种为其他 CTD,LP=0.006×管袢长/50+ 0.237×袢周积分。管袢长及袢周积分与肺动脉高压呈正相关。该预测模型通过列线图进行展示(图1),结果显示,管袢长每增加50 μm,列线图模型评分增加8分;袢周积分每增加1分,列线图模型评分增加3.5分;若患者为SSc/MCTD,列线图模型评分为 0;若患者为其他CTD,列线图模型评分为26分。
为了验证列线图模型对结缔组织病患者发生 PAH 风险预测的准确性,本研究绘制了该模型的 ROC曲线(图2)。ROC曲线结果显示,该模型的曲线下面积(area under the curve,AUC)值为0.705(P <0.05,95% CI:0.618~0.792),灵敏度 0.59(0.49~0.69),特异度 0.79(0.68~0.90),Cut ⁃ off 的分数是 0.314。表明该模型能较大程度预测 PAH 的发生。在此基础上,对该模型进行校准并绘制校准曲线(图3)。平均绝对误差(median absolute deviation, MAD)=0.027,均方误差(mean square error,MSE)= 0.00109。校准曲线斜率近1,说明模型预测CTD患者发生PAH与实际发生风险一致性较好。
1CTD⁃nonPAH与CTD⁃PAH组患者临床资料比较
Table1Clinical characteristics between the CTD⁃nonPAH and CTD⁃PAH groups
(续表1)
CTD:connective tissue disease;SLE:systemic lupus erythematosus;SS:Sjögren’s syndrome;SSc:systemic sclerosis;RA:rheumatoid arthritis; OCTD:undifferentiated connective tissue disease;MCTD:mixed connective tissue disense;PVR:pulmonary vascular resistance;CO:cardiac output;CI: cardiac index;mRAP:mean right atrial pressure;SvO2:venous oxyhaemoglobin saturation;RBC aggregation:red blood cell aggregation.
2Logistic回归分析CTD患者发生PAH危险因素
Table2Logistic regression analysis of risk factors for the development of PAH in patients with CTD
2.4 不同危险分层的PAH患者甲襞微循环的临床特征
根据 2021 年“中国肺动脉高压诊断与治疗指南”推荐采用危险分层量表作为PAH患者危险分层评估模型[17],将 CTD⁃PAH 组 52 例患者进行危险分层,其中低危患者 13 例、中危患者 24 例、高危患者 15例,各组间的甲襞微循环特征仅乳头下静脉丛差异有统计学意义,管袢长及袢周积分差异无统计学意义(表3)。
1Nomogram构建CTD患者发生PAH风险预测模型
Figure1Nomogram for predicting the risk of PAH development in patients with connective tissue disease
2CTD患者PAH风险模型ROC曲线
Table2ROC curve for the risk model of PAH in patients with CTD
3CTD⁃PAH风险模型校准曲线
Figure3Calibration curve for the CTD⁃PAH risk model
3 讨论
PAH是CTD患者中常见且严重的并发症,显著影响生存率和生活质量[3]。研究表明,CTD 合并 PAH 患者的 5 年生存率显著低于未合并 PAH 的患者,且 PAH 是 CTD 患者死亡的主要原因之一[3-4]。因此,早期识别CTD患者中的PAH风险具有重要的临床意义,这不仅有助于改善患者预后,也为制定个体化治疗方案提供科学依据。
NVC 作为一种易操作、非侵入性的诊断工具,已逐渐应用于 CTD 患者微血管病变的识别与评估[1118-19]。Hofstee等[20] 于2009年首次提出,通过 NVC可用于SSc患者PAH风险的识别及预后预测,提出了“硬皮病模式”在SSc患者PAH发生的作用机制。然而,与西方以 SSc 为主的 CTD⁃PAH 患者不同,本研究CTD⁃PAH队列中SLE患者比例更大,反映了不同人群中疾病特征的异质性[4]
在本研究中,通过 NVC 发现本中心 CTD⁃PAH 患者较非PAH 患者表现出显著延长的毛细血管管袢长、较粗的毛细血管管径以及更高的毛细血管袢周积分。进一步构建了基于管袢长和袢周积分的风险预测模型,证实其对CTD患者发生PAH具有良好的预测作用。
毛细血管管袢长和毛细血管管径是评估甲襞微循环的重要参数,先前已有研究证实这两项指标与CTD⁃PAH发生风险密切相关[21]。毛细血管管袢长的异常延长常见于CTD患者,尤其是在SLE患者中,通常反映微血管壁重构和内皮细胞增殖异常[22-23]。这些病理改变使微血管床结构不稳定,毛细血管管袢的延长被认为是CTD患者早期PAH风险的预警信号之一[23]。本研究进一步表明,CTD⁃PAH患者的毛细血管管袢长显著长于无PAH患者,提示其可能与PAH的发生有重要关联。此外,毛细血管管径的增加,尤其是管径均一性扩张,反映了血管壁的炎症充血和内皮细胞增生[24],这些特征是PAH过程中微血管损伤的表现,且毛细血管管径扩张与肺血管阻力增加密切相关[25-26],这些病理过程增加局部血管的通透性,进一步加重血流异常分布,可能促成 PAH的发生。
毛细血管袢周积分是评估甲襞微循环异常的重要指标之一[5],主要反映毛细血管周围区域的炎症、渗出以及微血管功能的病理变化。在CTD患者中,免疫系统的持续激活会导致全身微血管损伤,而毛细血管袢周积分增加则是这些炎症和血管损伤的直接反映。显著增加的毛细血管袢周积分通常伴随毛细血管周围组织的炎症浸润、血管壁增厚及异常渗出,这些改变均与PAH的病理过程密切相关。研究显示,毛细血管袢周积分的显著增加与 CTD⁃PAH发生风险之间存在显著相关性[27]。SSc患者中,毛细血管周围的渗出和炎性改变被认为是 PAH发生的高危标志[24],这些病理改变会导致肺动脉阻力增加,进一步促进PAH的发生。
甲襞微循环不仅受CTD本身的影响,还可能受到多种因素的干扰,例如年龄、性别、生活方式(如吸烟、饮酒等)、心血管疾病及代谢性疾病等[162528-29]。此外,患者的甲床厚度、皮肤色素沉着、检测时的环境温度、血压及紧张等因素也会影响检测结果[8]。为提高研究结果的可靠性,本研究通过控制环境温度、实施标准化宣教等措施减少外界干扰,并通过控制患者的年龄、性别等混杂变量,从而有效提升结果的可信度。
3不同危险分层CTD⁃PAH患者甲襞微循环特征
Table3Capillaroscopic parameters in CTD⁃PAH patients across various risk stratifications
(续表3)
For the abbreviations,please see those in Table 1.
由于样本量的限制,本研究所构建的预测模型尚未得到验证,目前仅为开发队列的研究。未来研究中将进一步扩大样本量,并开展多中心研究,力争完善该预测模型,增强结果的普适性,并探索甲襞微循环在CTD⁃PAH预后中的潜在价值。
利益冲突声明:
所有作者均声明不存在利益冲突。
Conflict of Interests:
The authors declare no competing interests.
作者贡献声明:
周张迪负责酝酿和设计实验、实施研究、采集数据、分析及解释数据、论文撰写;张译心、戴嘉懿、李冬玉负责采集数据、分析及解释数据、统计分析;孙晓萱负责酝酿和设计实验、实施研究、对文章的知识性内容作批判性审阅;王嫱负责酝酿和设计实验、实施研究、对文章的知识性内容作批判性审阅、研究经费支持。
Authors Contributions:
ZHOU Zhangdi was responsible for conceiving and design⁃ ing the experiments,conducting the study,collecting data,ana⁃ lyzing and interpreting the data,and writing the manuscript; ZHANG Yixin,DAI Jiayi,and LI Dongyu were responsible for collecting data,analyzing and interpreting the data,and perform⁃ ing statistical analysis. SUN Xiaoxuan was responsible for con⁃ ceiving and designing the experiments,conducting the study, and critically reviewing the intellectual content of the article. WANG Qiang was responsible for conceiving and designing the experiments,conducting the study,critically reviewing the intel⁃ lectual content of the article,and researching funding support.
1Nomogram构建CTD患者发生PAH风险预测模型
Figure1Nomogram for predicting the risk of PAH development in patients with connective tissue disease
2CTD患者PAH风险模型ROC曲线
Table2ROC curve for the risk model of PAH in patients with CTD
3CTD⁃PAH风险模型校准曲线
Figure3Calibration curve for the CTD⁃PAH risk model
1CTD⁃nonPAH与CTD⁃PAH组患者临床资料比较
Table1Clinical characteristics between the CTD⁃nonPAH and CTD⁃PAH groups
2Logistic回归分析CTD患者发生PAH危险因素
Table2Logistic regression analysis of risk factors for the development of PAH in patients with CTD
3不同危险分层CTD⁃PAH患者甲襞微循环特征
Table3Capillaroscopic parameters in CTD⁃PAH patients across various risk stratifications
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